Artificial Intelligence
Unsupervised learning
Evolving neural networks through augmenting topologies
Evolutionary Computation
Coevolution of active vision and feature selection
Biological Cybernetics
Active Vision and Receptive Field Development in Evolutionary Robots
Evolutionary Computation
Neural Networks - 2005 Special issue: IJCNN 2005
Evolutionary active vision toward three dimensional landmark-navigation
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
Evolution of central pattern generators for bipedal walking in areal-time physics environment
IEEE Transactions on Evolutionary Computation
Analog Genetic Encoding for the Evolution of Circuits and Networks
IEEE Transactions on Evolutionary Computation
Creating Brain-Like Intelligence
Creating Brain-Like Intelligence
| Hi-index | 0.00 |
Complex visual tasks may be tackled with remarkably simple neural architectures generated by a co-evolutionary process of active vision and feature selection. This hypothesis has recently been tested in several robotic applications such as shape discrimination, car driving, indoor/outdoor navigation of a wheeled robot. Here we describe an experiment where this hypothesis is further examined in goal-oriented humanoid bipedal walking task. Hoap-2 humanoid robot equipped with a primitive vision system on its head is evolved while freely interacting with its environment. Unlike wheeled robots, bipedal walking robots are exposed to largely perturbed visual input caused by their own walking dynamics. We show that evolved robots are capable of coping with the dynamics and of accomplishing the task by means of active, efficient camera control.